I really don't see the big issue, can see it could be confusing to some. Personally I don't look at BOM forecasts. It is interesting to discuss the probability of rainfall though. Just seems when things don't go as expected the first place to blame is those forecasts instead of discussing why things did not turn out as expected. Other people have put it really well about the high expectations of forecasts I'm guilty of it aswell. Just don't see the need to go on a witch hunt over a failed forecast which in all fairness wasn't that far out.

I feel there are some improvements that can be made..... i.e there is a scattered degree of ambiguity and isolated chance of misinterpretation in the current forecast.

On a serious note however, I think the BOM do an excellent job in the vital service they provide. There are subtleties in the forecast description that are not apparent to the lay person. I feel less confident with the forecast than in previous years.

I'm by no means a weather expert and therefore the forecast should be tailored to someone like me. Without making drastic changes a few small tweaks may allay the frustration of many.

From these results , it's a perfect reflection of what BIGT said of previous page.

61% have no logic and can can not understand numbers or % 30% have logic and can work out % in there head in a second or so. 4%.....arrrrrr please explan the question agian

Thats a bit harsh isn't it?

One of the few problems with this method of forecasting is every now and again its contradictory. However at a glance you can see how much rain is likely to fall, how localised/liberal the rain will be (depending on how close together the two rainfall values are), and how likely it is to rain, in a succinct and precise way. My problem with the last week's forecasting was that the information given was contradictory, however by and large it was correct (btw I chose the undecided option). For example on a couple of days there was a forecast of 95% of rainfall, suggesting widespread rain for the vast majority of areas, there was a rainfall range of 1-2mm indicating fairly liberal rain, yet the rainfall was almost always going to be convective, and with the low shear the rainfall was therefore always going to be patchy, which is a contradiction of the bom's forecast. The average rainfall for said day over the NR region probably was 1-2mm, but many places received 0, yet a few places recieved some more lumpy totals, so the BoM technically correct.

Another common contradiction (well I see it as that anyway) is when the forecast is (say) 70% chance of rain, 0-4mm. So according to that there is a 70% chance of 0.02mm or more, yet theres a 50% chance of receiving 0mm (as the bottom number indicates a 50% chance of receiving that amount of rainfall, in this case 0), which doesn't add up. If I'm interpreting this wrong someone please let me know.

Apart from that, this forecasting system is very easy to use, and gives all the information needed in a nice compact couple of words. By and large the BoM do a very good job.

Providing a range-less 20% chance of Zero must be balanced by 80% chance of non zero, which means it's going to rain somewhere, with a certainty of 80%. Feel free to try and math the rain out of that logic.

At that specific location, there's a 20% chance it will rain (Rain = 0.2mm or more). 80% chance it will be dry. With a reminder of what the possible rainfall amounts on Bureau-produced forecasts mean (I know I'm rehashing a bit here but others may not know or have not noticed in the past):At a specific location (e.g. Happytown), the 'Possible Rainfall':1 to 3mm = 50% chance of 1mm or more, 25% chance of 3mm or more20 to 25mm = 50% chance of 20mm or more, 25% chance of 25mm or more2 to 15mm = 50% chance of 2mm or more, 25% chance of 15mm or more5 to 35mm = 50% chance of 5mm or more, 25% chance of 35mm or moreOn storm days there is a tendency to see possible rainfall amounts having larger ranges (like the last two examples), reflecting the localised nature of convective precipitation.If just "0mm" is used in the rainfall range, it indicates there is less than a 25% chance of 0.2mm or more, otherwise 0-0.2mm would be used (which would then indicate 25% of 0.2mm or more) or some other range, e.g. 0-0.4mm, 0-1mm. In other words, the chance of rain is very low, and that location should strongly expect no rain and (in this case) mostly sunny conditions. So with that in mind and because we can't have "negative rainfall", if there is a Zero present in the Possible Rainfall section:0mm = A 50% chance *or less* of getting more than 0mm, *less than* 25% chance of 0.2mm or more (otherwise 0.2mm would be shown like in the next example)0 to 0.2mm = A 50% chance *or less* of getting more than 0mm, 25% chance of 0.2mm or more0 to 5mm = A 50% chance *or less* of getting more than 0mm, 25% chance of 5mm or moreIf there is higher than a 50% chance of getting more than 0mm, because it exceeds the 50% probability threshold, then you may instead expect to see something like:0.2 to 1mm = 50% chance of 0.2mm or more, 25% chance of 1mm or more0.4 to 4mm = 50% chance of 0.4mm or more, 25% chance of 4mm or more

I should note Weatherzone's Opticast seems to use a different approach to determining the rain amount expected with less flexibility in it's rainfall ranges, so don't use the Bureau's 50%-25% probabilities on the possible rainfall (on WZ there is the option to change the source on most town forecasts and also hovering over the info with your mouse will identify its source). Some places also get there rain amounts from BOM OCF on WZ Forecasts which also seems to use a different approach. However, the pic above though appears to be the BOM rainfall amounts that you get from the normal Bureau-produced forecasts (which have guidelines available on what the thresholds are), but just using WZ graphics instead, so the probability ranges are applicable in this case.

A probability forecast includes a numerical expression of uncertainty about the quantity or event being forecast. Ideally, all elements (temperature, wind, precipitation, etc.) of a weather forecast would include information that accurately quantifies the inherent uncertainty. Surveys have consistently indicated that users desire information about uncertainty or confidence of weather forecasts. The widespread dissemination and effective communication of forecast uncertainty information is likely to yield substantial economic and social benefits, because users can make decisions that explicitly account for this uncertainty.

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Uncertainty can be expressed in ways other than probabilistic terms, such as odds or frequencies. But studies by social scientists have indicated repeatedly that expressing uncertainty in qualitative terms, such as “likely,” creates unnecessary ambiguity, with one user interpreting the same term as reflecting a higher probability than would another user.

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One highly desirable property of any probability forecast is that it be “reliable” (or “well-calibrated”). For instance, over the long term, precipitation should occur on approximately 20% of the occasions for which the forecast probability is 20%.

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The definition of the event being forecast must be clearly understood in order for probability forecasts to be communicated effectively and acted upon appropriately. For example, for a forecast of 30% probability of precipitation for Boston tomorrow, a person may be unsure as to whether that means: (a) it will rain over 30% of the Boston area tomorrow; (b) it will rain for 30% of the time tomorrow somewhere in Boston; (c) there is a 30% probability it will rain somewhere in Boston tomorrow; or (d) at any given location in the Boston area, there is a 30% probability that it will rain tomorrow. The definition of a precipitation event used by the NWS is measurable precipitation within the stated time period at any point in the area for which the forecast is valid (i.e., (d) is the correct answer).

Use of probabilities can sometimes cause some confusion, and many people are more familiar with Odds which are commonly used for betting. The two are very closely related. For example, a probability of 10% means 10 times out of 100, or a 1 in 10 chance. Thus for every 10 occasions the event will not occur on 9 occasions and will only occur once. The Odds are therefore 9:1 against. Working in the opposite direction, if the Odds are 4:1 against an event occurring, then this means that it will not happen 4 times as often as it happens. So it will occur on 1 occasion in 5. Turning 1 in 5 into a percentage gives 20%.

It is important to remember that the reason for issuing probability forecasts is that it is often impossible to give a categorical yes/no forecast with complete accuracy. A probability forecast instead describes how likely an event is on a particular occasion. Thus it is reasonable to ask whether a probability forecast can be wrong. For example, if a probability is given as 10% and the event occurs, then is this right, or wrong? One might think that it is wrong because the probability was low but the event did occur, but this is the wrong interpretation. Of all the times that a 10% probability is issued, the event should happen 1 time in 10. Thus we can never say whether a single probability forecast is right or wrong. We can only measure how good our probability forecasts are by looking at a large set of forecasts. Then we can group all the 10% forecasts together and check that the event occurred on 1 in 10 of these occasions; similarly for the 70% forecasts, it should occur on 7 in 10, etc. Results from verifying a large number of forecasts can be plotted in a Reliability Diagram.There is one rather trivial exception to the general rule that probability forecasts cannot be wrong. The only time a single forecast can be wrong is if the issued probability is either 0% or 100%, which is equivalent to going back to a categorical forecast, and getting it wrong!

Probabilistic forecasting is a technique for weather forecasting that relies on different methods to establish an event occurrence/magnitude probability. This differs substantially from giving a definite information on the occurrence/magnitude (or not) of the same event, technique used in deterministic forecasting. Both techniques try to predict events but information on the uncertainty of the prediction is only present in the probabilistic forecast."...Think about how you do a forecast. The internal conversation you carry on with yourself as you look at weather maps is virtually always involves probabilistic concepts. It is quite natural to have uncertainty about what's going to happen. And uncertainty compounds itself. You find yourself saying things like "If that front moves here by such-and-such a time, and if the moisture of a certain value comes to be near that front, then an event of a certain character is more likely than if it those conditions don't occur." This brings up the notion of conditional probability. A conditional probability is defined as the probability of one event, given that some other event has occurred. We might think of the probability of measureable rain (the standard PoP), given that the surface dewpoint reaches 55F, or whatever...."

Perhaps it's in human nature to be uncomfortable with not being able to blame someone or something for a perceived fault (possibly a kind of coping mechanism given emotions often get involved when it comes to weather?). With the previous kind of forecast, it was easier to take out one's frustrations about missing the rain or storms and blame the Bureau for what one may believe to be an incorrect forecast. In assessing the performance of probability forecasts, it requires a shift in thinking, you have to judge the errors over the long term.At home over a long period of time (e.g. a year or more), you could take note of how many times it rains (meaning 0.2mm or more, and without a gauge of your own approximately when the concrete/pavement becomes totally wet by raindrops would be a good enough comparison) at each percentage level. I believe forecasts are done down to a 6km x 6km grid in NSW & QLD (3km x 3km in VIC & TAS). 6km x 6km is about the dimensions of a large country town (e.g. Warwick, Armidale), or if in the city / urban area: your suburb plus at least the next ring of suburbs (and maybe including the second ring of suburbs from your suburb if nearer to the inner city or have small suburb sizes in your urban area). So if the rain missed your house but maybe affected an adjacent suburb/neighbourhood you'd have to make a judgment call based on the radar, nearby obs (if available), or the thickness of the rain curtain as to whether 0.2mm or more fell. What you'd hope to find over the long-term is that it only rains about 10% of the time when 10% chance of rain is given, about 50% of the time when 50% chance of rain is given, and about 90% of the time when 90% chance of rain is given etc. It should never rain with 0% chance of rain forecast and it should always rain with 100% chance of rain forecast (with a reminder that rain = 0.2mm or more).

It would seem unlikely that they will go back to the previous style of forecast. They found that the "Patchy rain", "Scattered showers and thunderstorms" and "Isolated showers and the chance of thunderstorms" forecasts etc., were too confusing and not being understood by most of the general public. They changed to probability forecasts with the aim of making it more simple and less confusing, and to satisfy the public's demands of 'how likely is it going to rain' and 'how heavy will the rain be'. It does seem like though that it doesn't matter what style of forecast they use, most people won't be happy with the Bureau until forecast accuracy is basically 100%. The Bureau also get a harder time from people over perceived incorrect forecasts because many see them as a faceless entity. They are more forgiving if a perceived forecast error comes from say somewhere like Higgins, other local FB weather pages, or other knowledgeable weather-folk elsewhere on the net, because often through interaction you build a personal connection with them (aside from the humanisation, the bans and the threat of a ban in some of these places probably play a part in reducing the criticism too).

As a normal layperson with limited weather knowledge, I often get frustrated in drought periods when we have a couple days of rain forecast and get nothing, it's devastating. You watch the farmers start preparing paddocks for crops etc banking on getting that rain. However this last rain period didnt really excite me much, I saw the forecast as scattered showers, there was no significant weather pattern I could see that suggested good widespread rain so I took it with a grain of salt. I think part of weather forecasting is for the customers to also realise when there's no dependable rain system that can be relied upon to deliver, it's only a possibility of rain. We've become too dependant on forecasts, though I understand why, weather is an important aspect of so many jobs.

I welcome the question, but this topic is more appropriate on the General Weather thread. Having said that, this has been a great discussion.

Anyhow, since you've raised it here, I must say that the BoM did not get the forecasting wrong for last week's 'hit and miss' showers/storm event. It was right according to its present forecasting protocols.

Logic dictates that if a percentage is given then, depending on its proportionality, the rainfall will be more likely than not one way or the other. However, I agree that terms such as isolated, scattered, or widespread would have helped to describe those percentages in language which is readily understandable to the general public.

I was surprised to hear that one of the reasons the BoM changed the previously terminology was that it failed to resonate with the general public who did not understand such terms. I'm sorry but my 6 year old grandson can understand these terms. We're not a society of dunderheads, surely.

If you want to dumb down such terms, perhaps 'not likely'; 'more likely than not'; or, 'very likely' would be better' to supplement the current percentages, which, as others have already stated, don't mean much to the numerically challenged. You need to make numbers speak, and numbers are just that without words to complement their significance.

Mostly sunny.Possible rainfall: 0 mm Chance of any rain: 10%Winds south to south westerly.Everyone knows that if Brisbane is to get south westerlies it virtually doesn't deliver any rain.Forecast is sunny on both sides of the ledger but they still put in 10% chance of rain which is ludicrous.It should just say 0% chance.It really should be 0% every day until Sunday.Samboz summed it up beautifully.

When we discuss this topic it is about questioning the current forecast policy(A Policy is not a person but a set of guidelines to be guided by), not the Bom personnel, so please keep that in mind.

Look at the Birdsville forecast this week. Ridiculous.Forecast is sunny on both sides of the ledger with 20% chance of rain.Plus the temp will be a billion degrees which is normal.Sorry but your normal joe won't carry around the guidlines with them to make a decision on what the forecast means.

The forecast should be,Fine and sunny, with a bit of virga which will never reach the ground